artificial - Blog - Global Risk Community2024-03-28T16:22:01Zhttps://globalriskcommunity.com/profiles/blogs/feed/tag/artificialHealthcare adopting Artificial Intelligence in a Rapid Wayhttps://globalriskcommunity.com/profiles/blogs/healthcare-adopting-artificial-intelligence-in-a-rapid-way2020-10-03T07:38:54.000Z2020-10-03T07:38:54.000ZKBV Researchhttps://globalriskcommunity.com/members/KBVResearch<div><p>Artificial Intelligence (AI) is an assessment to imitate human intelligence into the technology of computers. The capacity of AI in medication has been communicated and proved by different experts in the industry. The capacity of AI techniques in medication and diagnosis are many. </p><p></p><p><a href="{{#staticFileLink}}8028339886,original{{/staticFileLink}}" target="_blank"><img src="{{#staticFileLink}}8028339886,original{{/staticFileLink}}" class="align-center" alt="8028339886?profile=original" /></a></p><p></p><p>Firstly, it gives an exploration center for the appraisal, association, representation, and classifying of clinical data. Secondly, it produces new instruments to support the dynamics of clinical, training, and research. Thirdly, it incorporates activities in medical, computer, psychological, and other various sciences. Fourthly, it offers a control-rich discipline for a future scientific medical specialty. Various intelligent structures have been made to enhance clinical consideration and diagnosis so as to provide a platform that reduces expenses, superior medical facilities, and others. </p><p>Living in the era of the fourth revolution of industry, innovation ends up being a blessing that no individual can avoid. The artificial intelligence is being used and relentlessly investigated to make it prepared for use in all spaces of life and even more noteworthy in the field of medicine where precision can mean decisive for a patient. There are numerous benefits to use <a href="https://www.kbvresearch.com/artificial-intelligence-diagnostics-market/">Artificial Intelligence in the medical diagnostic</a> frameworks. </p><h2>Let’s Know more about Artificial Intelligence in Diagnosis</h2><p>It has been acknowledged by different specialists and doctors that Artificial Intelligence innovation has numerous advantages over other traditional practices due to the way that it can explore massive datasets simultaneously, gives us an independent revelation that uncovers hidden patterns, and furthermore redesigns the speed by suggesting auto-created clinical pathways. <strong>Artificial Intelligence is an instrument that can support doctors and specialists in early finding and help cut down the death rate and medical inflation.</strong> </p><p>Diagnosis is the way toward transforming observed evidence into the names of diseases. The principal to the effective delivery of medical services by the specialist is the complex ability of clinical problem-solving. The accuracy of this ability is basic to the life and wellbeing of his/her patients. The adequacy with which it is applied is of extraordinary economical significance. Applying Artificial Intelligence (AI) strategies in the clinical field may help not simply in improving the accuracy performance of classification but also in saving diagnostics' time, cost, and the pain associated with pathologies' tests. </p><p>There are numerous applications of Artificial Intelligence that vary from image acquisition, aided processing of reporting, data mining, follow-up, and information storage, and so on. The use of AI includes computational models and algorithms that emulate the biological neural network architecture of the brain, i.e., artificial neural networks (ANNs). Based on Output, Deep learning has a lot more prominent success pace when compared with conventional machine learning. </p><h2>Future Outlook: </h2><p>The future of diagnosis will be better and better. The utilization of the incorporation of PCs and artificial intelligence can change the world of clinical diagnosis. Growth in innovation will demonstrate as a solid platform for the development of the utilization of artificial intelligence in diagnosis. </p><p>Artificial Intelligence (AI) has grown rapidly since the late 1980s. Growing clinical care datasets and its performance, the past twenty years have seen significant development in publication on AI. However, with the introduction of extended computational power, the availability of AI devices has been expanded. There are two primary devices in AI, machine learning, where structured data (for instance pictures, EP, and genetic data) is inspected, and natural language handling, where unstructured data is analyzed. </p><p>Both AI devices have been improved in significant detail throughout late decades for their procedures, algorithms, techniques, and applications. However, various endeavors and new techniques for AI have been used in recent years, and a few diseases; for instance, cancer, nervous system disease, cardiovascular disease, liver disease, congenital cataract disease, etc were potentially analyzed using AI. Currently, an advanced strategy called deep learning has created a booming impact of AI and phenomenal modifications on diagnostic medical imaging frameworks like endoscopic diagnostic, pathology, and dermatology will be foreseen to develop in the coming years. </p><p>Neurology had dominated the utilization of artificial intelligence in diagnosis. Radiology is foreseen to be the fastest-growing section in light of the improvement of AI-based applications utilized for diagnostic imaging. The diagnosis that depends on artificial intelligence incorporates early identification and precise diagnosis of different neurological issues, for example, autism, Alzheimer's disease, Parkinson's disease, ischemic stroke, and multiple sclerosis. </p><h2>Summary:</h2><p>Attributable to expanding development and advancements in machine learning techniques like artificial intelligence has made its way into medical diagnostic frameworks. Because of the various advantages of Artificial Intelligence in diagnosis will help in the development of this market. Understanding the circumstance in India, low awareness with respect to health among the population consistently defers treatment bringing about the aggravation of protected people's medical conditions. When treatment occurs, private experts are inclined to use pointless medical procedures and related techniques. </p><p>Hence, it is very evident that managing this region isn’t a simple task when various components are ruling the graph of this industry. This is where Artificial Intelligence comes in, with the help of these computerized diagnosis algorithms pointless treatment can be avoided consequently cutting down the inflation.</p></div>Artificial Intelligence and Deep Learning are Transforming Modern Erahttps://globalriskcommunity.com/profiles/blogs/artificial-intelligence-and-deep-learning-are-transforming-modern2020-08-15T06:57:29.000Z2020-08-15T06:57:29.000ZBhupendra Prasadhttps://globalriskcommunity.com/members/BhupendraPrasad<div><p>Ever since the invention of machines or computers, their ability to do difficult tasks grew significantly. The recent growth in computer and machine algorithms has changed the face of engineering and science. The growth is so tangible that it is significantly rebuilding relationships among people, organizations, intelligent behavior, and engineered systems.</p><p></p><p><a href="{{#staticFileLink}}8028329270,original{{/staticFileLink}}" target="_blank"><img src="{{#staticFileLink}}8028329270,original{{/staticFileLink}}" class="align-center" alt="8028329270?profile=original" /></a></p><p></p><p>The computer systems have been developed to increase the speed and reduce size in terms of time. The curiosity of humans has pushed them to wonder “Can a controlled system or machine think and behave like humans?”</p><p></p><p>Probably such curiosity had led to the invention of modern machine learning systems such as Artificial Intelligence. Before we dig deep into the subject, let’s first understand what Artificial intelligence is.</p><p></p><h2><strong>What is Artificial Intelligence?</strong></h2><p>In 1956, John McCarthy had coined the term <strong>Artificial Intelligence</strong> (AI). A commonly believed notion that “<em>Machine will think and do like humans more accurately in the near future</em>” is the concept behind Artificial Intelligence. In other words, AI can be defined as “the engineering and science of making intelligent machines, especially computer programs”.</p><p></p><p>AI is similar to making a computer or software that thinks intelligently and in same manner as intelligent humans. On the other hand, <strong>Deep Learning</strong> is a subset of Artificial Intelligence that emulates the functioning of the human brain in processing data for use in making decisions, detecting objects, recognizing speech, and translating languages. Deep learning methods can work without human supervision.</p><p></p><h2><strong>Why AI is gaining Massive Popularity?</strong></h2><p>The Digital era has brought about an explosion of data in varied forms and from different regions of the world. This data is known as big data that is taken from different search engines, social media, e-commerce platforms, and other digital sources, etc.</p><p></p><p>In this, there is a huge amount of unstructured data that would take decades for humans to understand and extract relevant information. Many companies realize the potential of AI systems like Deep Learning in unraveling this wealth of data into easy to understand format.</p><p></p><p>There is a positive correlation between the popularity of AI and its growing advantageous applications to vast fields.</p><p>Now, let’s dive deep into the applications of AI to different fields because of which Artificial Intelligence is gaining massive popularity.</p><p></p><p>If you’re seeking to enhance your skills and career prospects, then nothing can be better than learning Artificial Intelligence. Extensive and exclusive courses on Artificial Intelligence are offered by <strong><em><a href="https://www.skillxs.com/">SkillXs</a></em></strong>.</p><p></p><h2><strong>Applications of Artificial Intelligence</strong></h2><p>Artificial Intelligence has a dominant role in various fields owing to its numerous beneficial applications.</p><p></p><h3><strong>1. Medicine</strong></h3><p>The evolutionary calculation is the term for some computational strategies in line with the ordinary growth process that mimics the system of common choice and survival of the fittest. Artificial Intelligence has been effectively helping PC to locate the tumors in therapeutic pictures. AI is similarly known to reach to the conclusion of various types of growth, and inborn heart surrenders.</p><p></p><h3><strong>2. Accounting Databases</strong></h3><p>AI is known to mitigate the problems of accounting databases. There are some issues with existing accounting database systems such as the needs of decision-makers are not fulfilled by accounting information, humans do not comprehend the computerized databases, and accounting systems are not easy to use, etc. Integrating AI systems with these databases can help in the appraisal of huge volumes of information with or without a leader’s support.</p><p></p><h3><strong>3. Gaming World</strong></h3><p>Playing games is one of the favorite things to do for many people. With the advancement of computer games, they have come a long way from modest text-based to the 3D graphics games with the complex universe. Today, AI is the most crucial part of any computer game. Playing the game without artificial intelligence would be so tedious. AI provides complex and new features to the gaming world. Spatial thinking, learning, audio use, assets portion, circumstance investigation, direction, rushing are some of the many different ways that AI adds to modern era computer games.</p><p></p><h3><strong>4. Traffic Signal Recognition</strong></h3><p>Various devices can perceive, recognize, and follow traffic signs from moving vehicles. Existing algorithms and systems cannot distinguish traffic signs. Locating and detection is done by AI methods based on color segmentation using different shape models. 3D technology is also often used. Other methods that use machine learning algorithms are also used for detection and classification.</p><p></p><h2><strong>Future Outlook</strong></h2><p>Using Artificial Intelligence with advanced research work, it would be possible to manage the roads’ traffic. Additionally, by applying different algorithms of AI, it would be possible to reduce the number of accidents that happen on the road.</p><p></p><p>Though AI has not touched the common people’s lives directly, but it is open to areas like neutral networks, medical, industry, space, military, and geology. With extensive research and advancement, we can expect bright forecasts in the field of AI and we will be able to move from the concept of humans like machines to developing the machinery that will be able to understand and act like intelligent humans.</p><p></p><p>That will be the era where robots based on AI will be doctors in hospitals, drivers in a bus, cook in restaurants, and professors in the classroom.</p><p>Experts of Artificial Intelligence predict that there will be 2.3 million jobs in the field of AI by 2020. Moreover, it is also predicted that AI technology will destroy around 1.7 million jobs worldwide, but still creating about half a million new jobs all over the world.</p><p></p><p>Additionally, AI offers various feasible and unique career possibilities. AI is used in various fields ranging from entertainments to transportation, yet there is a dearth of skilled and qualified professionals.</p><p>Hence, we can conclude that careers in AI technology can take a person to great heights in terms of growth, stability and money.</p><p></p><h2><strong>To conclude</strong></h2><p>There is extensive research going on in the field of Artificial Intelligence and Deep Learning. The domain of AI gives machines the ability to think intelligently and analytically. There is a huge contribution of AI techniques to various areas. AI would positively play a vital role in different fields in the coming future. AI techniques are used in computer games to make them more user-friendly. Moreover, AI plays a vital role in managing traffic signals and reducing the number of accidents on the road.</p><p></p><p>Owing to vast applications, it is pertinent to say that the field of AI will flourish more in the times to come. It is not wrong to say AI would be going to attract the attention of aspirants, researches, and the common people to a great degree in coming future.</p><p></p><p>Mastering Artificial Intelligence and other digital courses become easy with <em>SkillXs</em>. You may click on the given below link to know more about the courses.</p><p></p><p><strong>To join course click here:</strong> <a href="https://www.skillxs.com/course/115/artificial-intelligence-and-deep-learning">https://www.skillxs.com/course/115/artificial-intelligence-and-deep-learning</a></p></div>I Ain't Blue, I am Different: The Innovation Leadership Mindsethttps://globalriskcommunity.com/profiles/blogs/i-ain-t-blue-i-am-different-the-innovation-leadership-mindset2020-04-01T06:00:00.000Z2020-04-01T06:00:00.000ZJoseph Robinsonhttps://globalriskcommunity.com/members/JosephRobinson808<div><p>Today’s C-suite is making a significant investment in new technologies. Yet, it is failing to achieve full value. Technologies are being<a href="http://flevy.com/blog/wp-content/uploads/2020/02/pic-1-Innovation-Leadership-Mindset-300x199.jpeg" target="_blank"><img src="http://flevy.com/blog/wp-content/uploads/2020/02/pic-1-Innovation-Leadership-Mindset-300x199.jpeg?profile=RESIZE_710x" width="300" class="align-right" alt="pic-1-Innovation-Leadership-Mindset-300x199.jpeg?profile=RESIZE_710x" /></a> deployed in pockets or silos without a Strategy for scaling the Innovation from these technologies across the enterprise. Unable to scale their Innovation, organizations are not realizing the full benefits of their technology investments.</p><p>An <a href="https://flevy.com/browse/flevypro/innovation-leadership-mindset-4037">Innovation Achievement Gap</a> exists. <em>What is the Innovation Achievement Gap?</em> This is the difference between potential and realized value from technology investments. When new technology does not achieve its full value, the Innovation Achievement Gap exists.</p><h3><strong>What Companies are Facing Today</strong></h3><p>The enormous challenge of <a href="https://flevy.com/browse/stream/innovation">Innovation Management</a> with legacy systems is facing companies today. The conventional IT stack is not built or designed for the world of tomorrow. These are our software applications, data, hardware, telecommunications, facilities, and data centers. Today’s cloud-oriented world is full of analytics. There are sensors, mobile computing, AI, the Internet of Things (IoT), and billions of devices. <a href="https://flevy.com/digital-transformation">Digital Transformation</a> is changing the face ob business.</p><p>True, companies have started in the cloud. But the systems have not been adopted at the pace of technological change. As a result, there are distinct Leaders and Laggards when it comes to the adoption and penetration of technologies. Leaders are seeing more than 2X the revenue growth of Laggards. Laggards, on the other hand, often adopt technologies as individual point solutions without a strategy for enabling systems than can achieve enterprise-wide, game-changing innovation. While they might have pockets of brilliance, Laggards cannot maximize the value achieved. To be a Leader is to have an Innovation Leadership Mindset.</p><p>Simply said, adopting technologies does not guarantee success. This requires a systematic and sequential strategy in line with Next-gen Enterprise Systems. This needs an Innovation Leadership Mindset.</p><h3><strong>Doing Things Differently: The Innovation Leadership Mindset</strong></h3><p>Leaders differ much from Laggards. Embedded within their whole being is the <a href="https://flevy.com/browse/flevypro/innovation-leadership-mindset-4037">Innovation Leadership Mindset</a>.</p><p><a href="https://flevy.com/browse/flevypro/innovation-leadership-mindset-4037" target="_blank"><img src="http://flevy.com/blog/wp-content/uploads/2020/02/pic-2-innovation-leadership-mindset.png?profile=RESIZE_710x" width="750" class="align-full" alt="pic-2-innovation-leadership-mindset.png?profile=RESIZE_710x" /></a></p><p>Having an Innovation Leadership Mindset is clicking the future into place. There are 4 core pillars of the Innovation Leadership Mindset. Let's define the first 2:</p><ol><li><strong>Invest in innovation</strong>. Leaders invest more in innovation. Organizations with Innovation Leadership Mindset direct a greater percentage of its IT budget toward innovation. They accelerate investment innovation over the next 5 years. Leaders are far advanced from Laggards when it comes to investing in innovations. Leaders invest 93% on innovation and are expected to increase this to 97% in the next 5 years. On the other hand, laggards invest only 64% on innovation with a planned investment of 74% in the next 5 years.</li></ol><ol start="2"><li><strong>Develop Innovation Systems</strong>. Leaders show a consistently higher rate of technology adoption. Organizations with Innovation Leadership Mindset adopt new technologies earlier and develop higher levels of expertise. They prioritize and sequence implementation in optimal ways. Leaders have been found to adopt a fundamental general-purpose technology at a rate of 98%. An example of this is <a href="https://flevy.com/business-toolkit/artificial-intelligence">Artificial Intelligence</a>. Laggards, on the other hand, have faith in a fast follower approach. They take technology haphazardly leading to patchwork across the organization.</li></ol><p>There are 2 other core pillars that are equally important. One is <strong>Scale Technology Innovation</strong> and the other is <strong>Evolve Next-gen Enterprise Systems</strong>. Leaders that set their sights on innovating at scale target 3 times more business processes with technologies. Leaders have also drummed up their resources towards building the Next-gen Enterprise Systems.</p><p>Next-gen Enterprise Systems are systems that are capable of repeatable and scalable innovations. It is Boundaryless, Adaptable, and Radically Human. Outpacing others calls for organizations to start envisioning their own version of Boundaryless, Adaptable, and Radically Human Next-gen Enterprise Systems.</p><p>Interested in gaining more understanding of the <a href="https://flevy.com/browse/flevypro/innovation-leadership-mindset-4037">Innovation Leadership Mindset</a>? You can learn more and download an <a href="https://flevy.com/browse/flevypro/innovation-leadership-mindset-4037">editable PowerPoint about the <strong>Innovation Leadership Mindset</strong> here</a> on the <a href="https://flevy.com/browse">Flevy documents marketplace</a>.</p><p><strong>Are you a management consultant?</strong></p><p>You can download this and hundreds of other <a href="http://flevy.com/pro/library/frameworks">consulting frameworks</a> and <a href="http://flevy.com/pro/library/consulting">consulting training guides</a> from the <a href="http://flevy.com/pro/library">FlevyPro library</a>.</p></div>Artificial Intelligence (AI) in Energy Market Analysis and Forecast 2019-2024https://globalriskcommunity.com/profiles/blogs/artificial-intelligence-ai-in-energy-market-analysis-and-forecast2019-12-24T12:30:00.000Z2019-12-24T12:30:00.000ZBIS Researchhttps://globalriskcommunity.com/members/BISResearch<div><p><a href="{{#staticFileLink}}8028305084,original{{/staticFileLink}}" target="_blank"><img src="{{#staticFileLink}}8028305084,original{{/staticFileLink}}" class="align-left" alt="8028305084?profile=original" /></a></p><p>The AI software segment currently holds the highest share of the global AI in the energy market (by product offering). AI software providers are responsible for maintaining and storing the application data of the customers. However, AI-as-a-service (AIaaS), also known as platform as platform-as-a-service, is one of the emerging AI product offerings, which allow the end users to access AI-enabled platform using cloud computing. AI-as-a-service is dependent on the purpose and application of the end user and works on the basis of “pay as you go” concept and on monthly or annual pricing subscriptions as well. AIaaS is provided by third-party vendors on which the end users can build their own application specific AI system with an access of cloud stack for data storage.</p><p><strong>Browse Full Report: "<a href="https://bisresearch.com/industry-report/artificial-intelligence-energy-market.html" target="_blank">Artificial Intelligence in Energy Market</a>"</strong></p><p>AI-as-a-service product offering is expected to display the maximum growth in the forecast period, 2019-2024. Presently, the AI technology providers in the energy market also offer support services as a product offering. The support services include maintenance and repair, training and consultation, and installation and integration, among others.</p><p><strong>Request the Sample @ <a href="https://bisresearch.com/requestsample?id=795&type=download">https://bisresearch.com/requestsample?id=795&type=download</a></strong></p><p><strong>Key Questions Answered in this Report:</strong></p><p>• What are the key trends and opportunities in the market pertaining to AI in energy?<br /> • What is the estimated global AI in energy market size in terms of revenue for the time period 2018-2024, and what is the expected compound annual growth rate (CAGR) during the forecast period 2019-2024? <br /> • What is the expected future outlook and revenue to be generated by the different types of product offerings including software, hardware, AI-as-a-Service, and support services?<br /> • What is the estimated revenue generated by AI solutions in both power and oil & gas industries for the time period 2018-2024?<br /> • What is the estimated revenue generated by AI solutions in different power industry streams such as generation, transmission, and distribution for the time period 2018-2014? <br /> • What is the estimated revenue generated by AI solutions in different oil & gas industry streams such as upstream, midstream, and downstream for the time period 2018-2024? <br /> • What is the estimated revenue generated by AI solutions in different applications of power and oil & gas industry for the time period 2018-2024? <br /> • What is the current market size and opportunities of AI solutions in energy industry across different regions including North America, Europe, Asia-Pacific, and Rest-of-the-World?<br /> • What are the major driving forces that are expected to increase the demand for the global AI in energy market during the forecast period?<br /> • What are the major restraints inhibiting the growth of the global AI in energy market?<br /> • What kind of new strategies are being adopted by the existing market players to expand their market position in the industry?<br /> • What is the competitive strength of the key players in the AI in energy market on the basis of analysis of their recent developments, product offerings, and regional presence?<br /> • How is the competitive benchmarking of the key AI focused IT companies in the energy market on the basis of analysis of their market coverage and market potential?<br /> • What is the funding and investment landscape in the global AI in energy market?<br /> • Which type of players and stakeholders operate in the market ecosystem of AI in energy, and what are their significance in the global market?<br /> • Which are the leading consortiums and associations in the global AI in energy market, and what is their role in the market?<br /> • How does the regulatory landscape differ in different regions for AI in energy?</p><p><strong>Key Companies in the Artificial Intelligence (AI) in Energy Market</strong></p><p>The prominent players in the artificial intelligence in energy market include IBM Corporation, Microsoft Corporation, Accenture Plc, Amazon Web Services, Inc., Intel Corporation, Oracle Corporation, SAP SE, Huawei Technology, Cisco Systems, General Electric Company, Rockwell Automation, C3.ai, AutoGrid Systems, HCL Technologies, and Wipro Limited.</p></div>Crop Protection Segment in Applications to Dominate the Artificial Intelligence in Agriculture Markethttps://globalriskcommunity.com/profiles/blogs/crop-protection-segment-in-applications-to-dominate-the2019-12-03T11:30:00.000Z2019-12-03T11:30:00.000ZBIS Researchhttps://globalriskcommunity.com/members/BISResearch<div><p><a href="{{#staticFileLink}}8028303473,original{{/staticFileLink}}" target="_blank"><img src="{{#staticFileLink}}8028303473,original{{/staticFileLink}}" class="align-center" alt="8028303473?profile=original" /></a></p><p>The global artificial intelligence in agriculture market (on the basis of product offering) is segmented into software, hardware, AI-as-a-Service, and support services. The software segment dominated the global artificial intelligence in agriculture market in 2018 and is anticipated to maintain its dominance in market size throughout the forecast period (2019-2024) with hardware and AI-as-a-Service experiencing higher growth rates.</p><p><strong>Browse the Complete Report: "<a href="https://bisresearch.com/industry-report/artificial-intelligence-agriculture-market.html" target="_blank">Artificial Intelligence in Agriculture Market</a>"</strong></p><p>The global artificial intelligence in agriculture market (on the basis of farming type) is segmented into field farming, livestock farming, indoor farming, and other farming type such as aquaculture. The field farming segment dominated the global artificial intelligence in agriculture market in 2018 and is anticipated to maintain its dominance throughout the forecast period (2019-2024).</p><p><strong>Request the Sample @ <a href="https://bisresearch.com/requestsample?id=783&type=download">https://bisresearch.com/requestsample?id=783&type=download</a></strong></p><p>The global artificial intelligence in agriculture market (on the basis of application) is segmented into crop protection, weather forecasting, precision farming, farm machinery automation, crop growth assessment, and other applications under the category crop, fruit, and vegetable farming. The market is also segmented into animal growth monitoring, animal health monitoring, and other applications under the category livestock and aquaculture farming. The crop protection segment dominated the global artificial intelligence in agriculture market in 2018. Applications such as farm machinery automation and precision farming (across crop and livestock) are anticipated to experience higher growth rates over the forecast period (2019-2024).</p><p>The global artificial intelligence in agriculture market by region is segregated under four major regions, namely North America, Europe, APAC, and Rest-of-the-World. Data for each of these regions has been provided by country. Interesting regional market dynamics have also been provided in the report.</p></div>How Is Video Surveillance Budding With Artificial Intelligence?https://globalriskcommunity.com/profiles/blogs/how-is-video-surveillance-budding-with-artificial-intelligence2019-09-18T13:13:24.000Z2019-09-18T13:13:24.000ZKBV Researchhttps://globalriskcommunity.com/members/KBVResearch<div><p>Due to its ability to reduce security staff and management workload, AI-based video surveillance and analytics are seeing an increase in acceptance. Using artificial intelligence technology in video analysis can offer companies substantial advantages in the identification and informing of unforeseen events. The key technologies that transform camera-based security systems include object recognition, face recognition, event recognition, remote asset management, intelligent image processing, and analytics.</p><h2>What is video surveillance?</h2><p>A digital surveillance device is a supervision system that captures pictures and videos which can be compressed, recorded, or transmitted via communication networks. For almost any workplace, digital <a href="https://www.kbvresearch.com/video-surveillance-market/">video surveillance</a> devices can be used. The primary distinction from the digital video surveillance system is that a digital video surveillance system can capture and store the video signal in digital format. As the information is recorded in a digital medium, any conversion is completely removed. Management from all over the world and interoperability is possible in most digital video surveillance systems. The cameras are networked and the images are recorded statistically, which for most companies is considered economical.</p><p><a href="{{#staticFileLink}}8028303659,original{{/staticFileLink}}" target="_blank"><img src="{{#staticFileLink}}8028303659,original{{/staticFileLink}}" class="align-center" alt="8028303659?profile=original" /></a></p><h2>Why is video surveillance a major necessity?</h2><p>Video surveillance systems have significant advantages for facility managers. Not only do security cameras decrease theft and loss, but they also have several other unique and unprecedented benefits. Owners can use all the distinctive features these devices give to make the most of the video surveillance of their facility. Video surveillance can offer the benefits you need to improve your properties' security, safety, and efficiency. In view of the upswing in smart devices, all gadgets are becoming more intelligent with no exception to these techniques. A substantial amount of cameras already operate readily with connected computers and are attached to Wi-Fi networks. However, cameras often don't come with built-in intelligence. Although the aspect of a large-scale security and surveillance system, at least until now, many cameras were not artificially intelligent.</p><h2>Artificial Intelligence and Video Surveillance</h2><p>The efficiency of surveillance technologies can be dramatically increased with artificial intelligence by bringing human attention to events that can compromise security through the transmission of real-time alerts. Intelligent video surveillance for incidents or objects of concern may be created. Even if a company has video footage, it is hard to identify specific incidents or persons during or after an event. With the power of artificial intelligence, facial recognition and identification of objects and activities are much easier, which enables real-time and proactive security.</p><p>Surveillance cameras can capture high-resolution pictures and videos, yet most devices do not use them for video surveillance. Most pictures or video recordings recorded by the operators are therefore of poor quality. This problem can discourage operators from producing accurate analytical reports and boost the likelihood of missed events. In this situation, image processing can be used to sharpen pictures and video recordings of low quality to simplify the acquirement of important information. Operators can readily assess improved pictures, decreasing the magnitude of unnecessary incidents.</p><p>Recent advances in video analytics - fueled by artificial intelligence technologies such as machine learning - enable computers to perceive and comprehend human-like surveillance images. Technologies of identification make it simpler to find who is in the pictures automatically. At last, the cameras themselves are more affordable, omnipresent, and much better; drone-mounted cameras can record an entire city. Computers can view all of the videos without any human issues, such as diversion, exhaustion, or training. The outcome is a monitoring standard that only a few years earlier was not possible.</p><p><strong>Click Free Insight:</strong> <a href="https://www.kbvresearch.com/news/video-surveillance-market/">https://www.kbvresearch.com/news/video-surveillance-market/</a></p><p><strong>In a Nutshell</strong></p><p>The video surveillance market is growing at a rapid pace. In recent years, video surveillance systems have been recognized as inevitable management tools for cities. The manager, without visiting the site, will be able to understand the location information. The surveillance system can improve the impact of management and supervision and reduce the likelihood of huge accidents. However, with the Internet of Things (IoT) generation, video surveillance technologies are faced with challenges such as mass access to hardware, big data, inadequate bandwidth, vulnerable attacks and difficulty in real-time monitoring. Probably, the security providers today have too many cameras and too many videos to keep up with. In addition, there are short periods of attention. AI is a technology which doesn't get bored, unlike humans, and which can analyze more video data than human beings could ever. It is intended to attract the attention of customers of the most important incidents and insights, enabling them to do their best: make critical choices. There are two fields in which video surveillance can have drastic effects on AI today: search and focus of attention. The swift development of the <strong>global video surveillance market</strong> is expected to speed at a growth rate of 14.6% CAGR over the forecast period.</p></div>The Power of Data and Analytics in Insurance Fraud Detectionhttps://globalriskcommunity.com/profiles/blogs/the-power-of-data-and-analytics-in-insurance-fraud-detection2019-09-17T12:22:33.000Z2019-09-17T12:22:33.000ZKBV Researchhttps://globalriskcommunity.com/members/KBVResearch<div><p>The problem for cyber security in the life insurance sector is very severe, as is the case in other sectors such as banking, healthcare, etc. The insurance industry has a huge amount of client data and clients have a lot of confidence in the organizations with whom they do business.</p><p></p><p><strong>What is insurance fraud detection?</strong></p><p>The <a href="https://www.kbvresearch.com/insurance-fraud-detection-market/">insurance industry</a> is moving to a contemporary paradigm that focuses on risk mitigation and prevention instead of financial loss compensation. This is driving the development of new insurance ecosystems and the latest generation of rivals. However, many insurers stay threatened by legacy infrastructure, siloed applications and absence of understanding on the importance of insurance analytics. This is exacerbated by M&A activities and by raising customer requirements for the use of new technologies. In addition to this, insurers are compelled to innovate in the field of consumer experience in business applications, such as mobile applications to create claims or self-service insurance analytics.</p><p></p><p><a href="{{#staticFileLink}}8028298899,original{{/staticFileLink}}" target="_blank"><img src="{{#staticFileLink}}8028298899,original{{/staticFileLink}}" class="align-center" alt="8028298899?profile=original" /></a></p><p></p><p><strong>What are insurance frauds and why are they increasing at a rapid rate?</strong></p><p>The technology breakthrough in recent years has led to a rise in insurance fraud and, as a result, the sector's landscape is evolving. From Pricing Comparison Websites (aggregators) to Telematics and Usage-Based Insurance, to the Internet of Things, to the growing demand for cyber insurance and recent Peer to Peer insurance, traditional insurers must rapidly adapt to current trends and compete with non-traditional companies with big data processing capacities.</p><p>On the other side, insurance companies are suffering from fraud expenses and, as insurance products become more complex and customer communication channels and potential fraudsters are rising. Furthermore, these trends are raising the level of intelligence and automation to combat insurance fraud overwhelms traditional fraud detection and avoidance of organizational structures, procedures, and technological infrastructure.</p><p></p><p><strong>How does insurance fraud detection save from the growing number of frauds?</strong></p><p>Big data analytics and artificial intelligence play a significant part in the insurance industry in this digital age. One of the major challenges for insurance companies seems to be detecting fraudulent insurance claims. The success of an individual fraudulent claim relies on the capacity of the fraudster to present it as a real, distinctive incident. Apparently, fraud has common features, which can be determined by exchanging information and analytics.</p><p>Insurance companies would all profit from entering forces and exchanging data through fraud pools. This is the only way to monitor, fight and control organized fraud. This would assist insurers to know about the recent fraud schemes and remain ahead of the game. Fraudsters are always searching for a weak place. Access to global fraud-related pools would discourage fraudsters from shuffling between countries and insurers.</p><p>Intelligent software can process data rapidly, learn individually, draw intelligent conclusions, and make recommendations. Just like a human, but smarter and more effective. The vast amount of information and the impressive computational capacity implies that these analyzes are carried out at lightning velocity and with excellent precision. For example, Artificial Intelligence can be used for analyzing images while at the same time digging for fraud. There are currently dozens of AI types in development. Insurance carriers may use these technologies to enhance and optimize their risk analysis and fraud identification procedures.</p><p></p><p><strong>Click Free Insight:</strong> <a href="https://www.kbvresearch.com/insurance-fraud-detection-market/">https://www.kbvresearch.com/insurance-fraud-detection-market/</a></p><p></p><p><strong>The bond between analytics and insurance fraud detection technologies</strong></p><ul><li><strong>Providing Client-centric Services</strong></li></ul><p>Customers are always looking for a trusted and reliable partner to meet their insurance requirements. Insurance Data Analytics helps insurance companies and brokers deliver tailored services to their customers. Companies can utilize intelligent insurance management platforms and other techniques to obtain useful insights from client information and provide customers with precisely what they are looking for.</p><ul><li><strong>Reducing Fraud and Waste</strong></li></ul><p>Fraud and waste are frequently seen and dealt with by insurance companies. Today, thanks to data analysis, there are methods to decrease these attempts at fraud to a significant degree. Insurance companies may use this data intelligence actionable to find out who is likely to be a fraudster even before it occurs.</p><ul><li><strong>Pricing Premiums Accurately</strong></li></ul><p>The significant challenge facing insurance companies is to price their premiums precisely for each policyholder. Often, policyholders may face unfair premium quantities for no error of their own. To be more competitive on the market, insurance companies are coming up with some new strategies using insurance analytics. The prices of premiums can be determined by drawing actionable ideas from data analytics and tracking the behavior of individual policyholders.</p><ul><li><strong>Managing Claims</strong></li></ul><p>With the assistance of data analytics, insurance companies can evaluate the large volumes of data and identify discrepancies in the underwriting phase of the policy. If the claim is made by the client, the insurer can readily detect that the claim is valid or not. Data analytics can be used to monitor digital channels and social media in real-time, and assist traditional insurance companies to transform their digital processes.</p><p></p><p><strong>To sum up</strong></p><p>The insurance fraud detection market is growing exponentially with the rise of analytics and artificial intelligence. Combining supervised and unsupervised machine learning as part of a wider fraud detection strategy for Artificial Intelligence (AI) allows digital companies to rapidly and precisely identify automated and progressively complicated fraud efforts. Among the most common types of new attacks, the adoption of machine learning and other automation techniques to commit fraud is emerging. The most popular legacy approaches to combating online fraud include relying on regulations and predictive models that are no longer efficient in facing the more advanced, nuanced levels of recent efforts at fraud. Online fraud detection requires AI to remain in tune with today's fraud attempts' rapid increase in complexity and sophistication. The <strong>global insurance fraud detection market</strong> is expected to proliferate at a growth rate of 26.6% over the forecast period.</p></div>High-End Synthetic Suede Market Analysis And Industry Size (2019-2029)https://globalriskcommunity.com/profiles/blogs/high-end-synthetic-suede-market-analysis-and-industry-size-20192019-07-11T12:30:00.000Z2019-07-11T12:30:00.000ZBIS Researchhttps://globalriskcommunity.com/members/BISResearch<div><p>The global high-end synthetic suede market is segmented into four major applications, namely automotive, fashion, furniture, and others. These applications are further sub-segmented based on their use of high-end synthetic suede. The global high-end synthetic suede market is growing at a rapid pace, owing to its enhanced functionality and properties compared to that of leather.</p><p><strong>Request the Sample @ <a href="https://bisresearch.com/requestsample?id=697&type=download">https://bisresearch.com/requestsample?id=697&type=download</a></strong></p><p>Another factor leading to increased adoption of synthetic suede is the high demand for lightweight material across industries such as automotive to improve their fuel efficiency. Various companies such as Fiat Chrysler, Daimler AG, and Porsche AG, among others, across the globe are actively adopting high-end synthetic suede in their production process.</p><p>In terms of value, the global <strong><a href="https://bisresearch.com/industry-report/high-end-synthetic-suede-market.html" target="_blank">high-end synthetic suede market</a></strong> (by application) was dominated by the automotive industry in 2018. The automotive industry segment accounted for a market value of $XX million in 2017 and is expected to reach a market value of $XX million by the end of 2029. The automotive industry is the highest demand generating application for the high-end synthetic suede market. The need for high-end synthetic suede across the automotive industry arises due to the need for lightweight material in order to increase fuel efficiency.</p><p><strong>Key Questions Answered in the Report:</strong></p><ul><li>What was the total revenue generated by the global high-end synthetic suede market in 2018 and how is it expected to grow during 2019-2029?</li><li>What are the major driving forces, trends, challenges and growth opportunities that can tend to influence the global high-end synthetic suede market during the forecast period, 2019-2029?</li><li>What was the revenue generated by the global high-end synthetic suede market, by application, such as automotive industry, fashion industry, furniture industry, and others in 2018, and how each segment is expected to grow by 2029?</li><li>What was the revenue generated by different regions, including Europe, Asia-Pacific, North America, and Rest-of-the-World (ROW) in the global high-end synthetic suede market in 2018, and how each segment is expected to grow by 2029?</li><li>Who are the key players present in the global high-end synthetic suede market?</li><li>What is the competitive strength of the key players in the high-end synthetic suede market on the basis of their recent developments, product offerings, and regional presence?</li></ul><p><strong>Related Reports:</strong></p><p><strong><a href="https://bisresearch.com/industry-report/global-3d-printing-software-services-market-2021.html" target="_blank">Global 3D Printing Software & Services Market – Analysis and Forecast (2017 to 2021)</a></strong></p><p><strong>About Us:</strong></p><p>BIS Research is a global market intelligence, research and advisory company which focuses on those emerging trends in technology which are likely to disrupt the dynamics of the market over the next five (or ten) years.</p><p>With over 150 market intelligence reports published annually, BIS Research focuses on various technology verticals such as 3D printing, advanced materials & chemicals, aerospace and defense, automotive, healthcare, electronics & semiconductors, robotics & UAV and other emerging technologies.</p><p>Each research report incorporates detailed analysis and subsequent quantification of- market dynamics, market drivers and restraints, opportunities, threats, market shares, current and emerging industry trends as well as detailed competitive landscape and intelligence.</p><p><strong>Contact:</strong></p><p><strong>39111 PASEO PADRE PKWY STE 313,</strong><br /><strong>FREMONT CA 94538-1686,</strong> <br /><strong>E-mail : sales@bisresearch.com</strong><br /><strong>Call Us : +1-510-404-8135</strong></p></div>The reality of AI: overcoming the hype to reach substancehttps://globalriskcommunity.com/profiles/blogs/the-reality-of-ai-overcoming-the-hype-to-reach-substance2019-05-02T11:23:15.000Z2019-05-02T11:23:15.000ZAndra Marinhttps://globalriskcommunity.com/members/AndraMarin<div><p>Setting aside the hype of AI and delivering real value for businesses is not easy. There are so many products and services touting to include ‘artificial intelligence’ as part of their offering, with almost ‘silver bullet’ potential, that there has to be an element of sympathy with IT leaders who are tasked with deciphering what is genuinely a good product, and what is merely a product that has just been rebranded and marketed as ‘AI’ but has the same fundamental capabilities it did five or even ten years ago.</p><p>They also have to do this in a situation where they are often being pressurised by an overly keen CEO, or more likely – they’re struggling to get board-level approval for AI. In fact, Corinium’s recent research of c-suite IT leaders in the US, found that the top barrier for AI adoption for respondents was getting board approval or buy-in (54%).</p><p>This may well be because of the perceived risk associated with taking on innovative technology – but perhaps the problem is deeper than this – it may even be the IT leader’s own fault. Why? Well, in most projects, when technology is involved, it is usually because there is a need for a solution, and it makes sense for a certain technology service or product to be implemented. According to our research, the smallest proportion (10%) said they would only investigate the use of AI in cases where the business is already seeking a solution for a specific use case. That suggests that technology leaders are looking for AI products before thinking about the solution they need it for, or they have thought a product could benefit the organisation in a way which they perhaps hadn’t thought about before. That doesn’t mean that this method is flawed – many innovative ideas come through chance rather than exploration. However, it does mean it may be harder to get buy-in for these ideas because of the perceived risk associated with AI solutions of this kind.</p><p>Other issues that may be holding back businesses from implementing AI could be a lack of resources or having archaic technology that would be hard to integrate into new AI products.</p><p><strong><a href="http://bit.ly/2UWchWx" target="_blank">The Unknowns</a></strong></p><p>Perhaps the biggest stumbling block for AI is actually how much is not known about it. For example, reading industry papers may make us think that data science is the most in-demand skill, but our C-level respondents actually picked out data analytics as the biggest requirement to exploit AI, while they also didn’t realise how much the HR department could benefit from AI, as it was the bottom ranked function, despite there already being capabilities like candidate screening in this space.</p><p>This ‘unknown’ part of AI is also impacting buy-in, and not just from CEOs and boards, but from employees. Employees may be scared of taking up AI, but that is almost entirely due to scaremongering – and perhaps even from what their own definition of AI is. Often, people think of AI as robots taking over the world, because of fiction books, TV and films, but the reality is that AI just enhances or automates mundane tasks, meaning employees can benefit in other ways.</p><p>The positive sign is though, that despite these holdbacks, IT leaders clearly believe there’s a future for AI in business. We’re still at the early stages of the technology really coming to the fore.</p><p><strong>To find out exactly what IT leaders including CIOs, CTOs and CDOs make of AI, download our full report here: <a href="http://bit.ly/2UWchWx" target="_blank">http://bit.ly/2UWchWx</a></strong></p><p> </p></div>Powering The Bionic Underwriter Of The Future (Webinar)https://globalriskcommunity.com/profiles/blogs/powering-the-bionic-underwriter-of-the-future-webinar-12019-03-06T11:30:00.000Z2019-03-06T11:30:00.000ZHamdallat Abdulsalamhttps://globalriskcommunity.com/members/HamdallatAbdulsalam<div><p dir="ltr"><span>Did you miss the live <span class="il">webinar</span>?</span></p><p dir="ltr"><strong><a href="https://www.brighttalk.com/webcast/16535/351002" target="_blank">Get the<span> </span><span class="il">webinar</span><span> </span>recording - “Powering The Bionic Underwriter Of The Future”</a></strong></p><p dir="ltr"><span>In this <span class="il">webinar</span>, you’ll get exclusive insights from:</span></p><ul><li dir="ltr"><p dir="ltr"><span>Susan Fallon, <em>Global Head of Commercial Property</em>, <strong>Zurich</strong></span></p></li><li dir="ltr"><p dir="ltr"><span>Alexandrina Scorbureanu,<em> Group Head of Projects & Overarching Activities</em>, <strong>ERGO</strong></span></p></li><li dir="ltr"><p dir="ltr"><span>Janthana Kaenprakhamroy, <em>CEO/Founder</em>, <strong>Tapoly</strong></span></p></li></ul><p dir="ltr"><span>Listen back to pick up tips, tricks and pointers on:</span></p><ul><li dir="ltr"><p dir="ltr"><span><strong>Leverage New Technologies, Tools And Techniques:</strong> Get to grips with the latest tools available to enhance the underwriting process, including sensor-based technologies and semantic web applications</span></p></li><li dir="ltr"><p dir="ltr"><span><strong>Move Beyond Existing Pricing Models: </strong>Identify ways to integrate new sources of data into the pricing process, and achieve pricing decisions that are statistically grounded in sophisticated analytics and rules-based decision support</span></p></li><li dir="ltr"><p dir="ltr"><span><strong>Develop Future Skills And Capabilities Now:</strong> Identify the new specialist skills that will complement core underwriting competencies, including data-driven product development, portfolio management and pricing analytics</span></p></li></ul><p dir="ltr"><strong><a href="https://www.brighttalk.com/webcast/16535/351002" target="_blank">Get the<span> </span><span class="il">webinar</span><span> </span>recording - “Powering The Bionic Underwriter Of The Future”</a></strong></p><p dir="ltr"><span>This <span class="il">webinar</span> was produced in the run up to <strong>Intelligent Automation & AI In Insurance Europe</strong> (May 21, London). Susan, Alexandrina, and Janthana will be joined at the conference by a whole host of expert speakers, to deliver the detail on how to unlock the artificial intelligence revolution for commercial lines.</span></p><p dir="ltr"><span>For more information on the agenda, speaker line up, and networking opportunities, download the detailed event brochure here: </span><strong><a href="http://bit.ly/2TkWbtM" target="_blank">http://bit.ly/2TkWbtM</a></strong></p><p dir="ltr"><span>I hope you enjoy the <span class="il">webinar</span> recording, and it would be great to see you in May!</span></p><p dir="ltr"></p><p dir="ltr">Warm Regards,</p><p dir="ltr"></p><p dir="ltr">Rachael</p><p dir="ltr"></p><p dir="ltr">Dr Rachael Gore</p><p dir="ltr">Head of Content</p><p dir="ltr">Intelligent Insurer</p><p dir="ltr">Direct: Tel: +44 203 301 8231</p><p dir="ltr"><span>Email: </span><a href="mailto:rgore@newtonmedia.co.uk?Subject=" target="_blank">rgore@newtonmedia.co.uk</a></p></div>marcus evans to Host the 2nd Edition Digital Transformation in Wealth Management Conference on September 24-26, 2018 in San Franciscohttps://globalriskcommunity.com/profiles/blogs/marcus-evans-to-host-the-2nd-edition-digital-transformation-in2018-05-03T15:14:36.000Z2018-05-03T15:14:36.000ZAmanda Pinkhttps://globalriskcommunity.com/members/AmandaPink<div><p><strong>marcus evans</strong> will host the <strong>2<sup>nd</sup> Edition Digital Transformation in Wealth Management Conference on September 24-26, 2018 in San Francisco.</strong> This conference will provide wealth managers with practical tools for developing a consistent and firm-wide digital adoption strategy allowing them to expand their client base and offerings. Industry experts will assess the best practices for leveraging and scaling robo-advice alongside traditional advice and how Artificial Intelligence (AI) and new digital capabilities can enhance financial planning and client onboarding processes.</p><p> </p><p><strong>Learn From Key Practical Case Studies:</strong></p><ul><li><strong>Charles Schwab</strong>will discuss where the wealth management industry is heading</li><li><strong>Invesco</strong> will assess the best practices for promoting a culture shift in wealth management</li><li><strong>BMO Financial Group</strong> will examine methodologies for improving client onboarding</li><li><strong>AgentRisk</strong> will explore where AI is bringing the most value to wealth managers</li><li><strong>CUSO Financial Services</strong> will evaluate practices for leveraging robo advice alongside traditional models</li></ul><p> </p><p><strong>Key Speakers Include:</strong></p><ul><li>Tobin McDaniel, Senior Vice President, Digital Advice, <strong>Charles Schwab</strong></li><li>Donie Lochan, Managing Director, Chief Technology Officer, Global Head of Technology, <strong>Invesco</strong></li><li>John Olerio, Senior Vice President, Director, Investment Services, <strong>Webster Investments</strong></li><li>Jon Vlachogiannis, Founder, <strong>AgentRisk</strong></li><li>Richard Keltner, Senior Vice President, Advisory Services, <strong>CUSO Financial Services </strong></li></ul><p> </p><p>For more information, please visit: <a href="http://bit.ly/2HJFBhf">http://bit.ly/2HJFBhf</a> or you can contact Amanda Pink at apink@global-fmi.com.</p><p> </p><p><strong><em>marcus evans</em></strong> <em>conferences annually produce over 2,000 high quality events designed to provide key strategic business information, best practice and networking opportunities for senior industry decision-makers.</em></p></div>7 Uses of Exponential Technology We’re Excited to Watch in 2017https://globalriskcommunity.com/profiles/blogs/7-uses-of-exponential-technology-we-re-excited-to-watch-in-20172017-02-15T04:11:57.000Z2017-02-15T04:11:57.000ZEnrique Raul Suarezhttps://globalriskcommunity.com/members/EnriqueRaulSuarez<div><p></p><p><a href="{{#staticFileLink}}8028249654,original{{/staticFileLink}}"><img width="450" src="{{#staticFileLink}}8028249654,original{{/staticFileLink}}" class="align-center" alt="8028249654?profile=original" /></a></p><p></p><h1 class="article-title" style="text-align:center;">7 Uses of Exponential Technology We’re Excited to Watch in 2017</h1><p style="text-align:center;"></p><p style="text-align:center;"><strong><span class="font-size-3">Source: Singularity University</span></strong></p><p></p><p style="text-align:center;"><span class="font-size-3"><em>This post was originally published on</em> <a href="http://singularityhub.com/2017/01/02/the-technologies-were-most-fired-up-to-watch-in-2017/" target="_blank"><em>Singularity Hub</em></a><em>. These excerpts that follow were written by Singularity Hub team members.</em></span></p><p style="text-align:center;"></p><p style="text-align:center;"><span class="font-size-3"><em><strong>By:</strong></em></span></p><p style="text-align:center;"></p><p style="text-align:center;"><span class="font-size-3"><em><strong>Alison E. Berman<br /></strong></em></span></p><p style="text-align:center;"></p><p style="text-align:center;"><span class="font-size-3"><a href="http://medium.com/@DigitAlison" target="_blank"></a></span></p><p><span class="font-size-3">Covering technology is exhilarating.</span></p><p><span class="font-size-3">Each year is filled with unforeseen surprises — advances we thought were years away, unexpected technology applications (like AI used for mental healthcare), and unlikely startups reimagining entire markets.</span></p><p><span class="font-size-3">These breakthroughs keep Singularity Hub’s team of tech-enthusiasts on our toes around the clock. Though we can’t forecast like famous futurist Ray Kurzweil, many of us have a favorite technology or two that we constantly track.</span></p><p><span class="font-size-3">Moving into the new year, these are some of the technologies we’ll be eagerly watching in 2017 and beyond.</span></p><h3><span class="font-size-3">1. Artificial Intelligence</span></h3><p><span class="font-size-3">“AI really made headlines this year. <a href="http://singularityhub.com/2016/02/06/how-googles-ai-beat-a-human-at-go-a-decade-earlier-than-expected/" target="_blank">AlphaGo</a> was on the tongue, <a href="http://singularityhub.com/2015/12/20/inside-openai-will-transparency-protect-us-from-artificial-intelligence-run-amok/" target="_blank">OpenAI</a> got a billion dollars to develop ethical AI, and toddlers talked to Google Home and Amazon Echo. (This generation won’t remember when they couldn’t converse with computers.) The first two developments are fascinating, but the third may be more immediately relevant. The idea of X product + AI will get legs next year — but it’s the surprises I’m most looking forward to.”</span></p><p><span class="font-size-3">–Jason Dorrier, Managing Editor</span></p><p><span class="font-size-3"><strong>Recommended reading:</strong> <a href="http://singularityhub.com/2016/10/26/the-ai-conversation-has-exploded-this-decade-with-big-advances/" target="_blank">The AI Conversation Has Exploded This Decade With Big Advances</a></span></p><h3><span class="font-size-3">2. Cybersecurity</span></h3><p><span class="font-size-3">“Cybersecurity means a lot of things to a lot of people, and often one person’s definition is at total odds with another’s. For me, I long for the type of unbeatable encryption promised by quantum computing, because quantum computing is going to make <a href="http://singularityhub.com/2016/11/24/quantum-computers-could-crush-todays-top-encryption-in-15-years/" target="_blank">today’s encryption</a> worthless. It’s something of a sinister race between computing power, encryption, and political motives. Meanwhile, billions of smart gadgets are coming online, and most of us already conduct our daily lives by digital means. With governments demanding access to digital devices and histories, I fear loss of citizen privacy, but still have faith in the democratization of cybersecurity.”</span></p><p><span class="font-size-3"><a href="http://medium.com/@matthewmagellan" target="_blank">Matthew Straub</a>, Digital Engagement Manager (the voice behind Singularity Hub’s social media)</span></p><p><span class="font-size-3"><strong>Recommended reading:</strong> <a href="http://singularityhub.com/2015/05/11/quantum-computing-is-about-to-overturn-cybersecuritys-balance-of-power/" target="_blank">Quantum Computing Is About to Overturn Cybersecurity’s Balance of Power</a></span></p><h3><span class="font-size-3">3. Decentralized Peer-to-Peer Networks</span></h3><p><span class="font-size-3">“I’m most excited about the future of decentralized peer-to-peer (p2p) networks. As we’ve seen with the sharing economy, it may be all too easy for a small startup to siphon the wealth of a local community sharing resources amongst themselves. We can use technologies like blockchain, cryptocurrencies and BitTorrent to redefine value by integrating blockchain-based democratic decision making, decentralized peer-run organizations, and organizational principles from platform cooperativism. Ultimately, as this trend continues, we’ll have an opportunity to regenerate local economies with the resources already available instead of extracting value where there isn’t much to begin with.”</span></p><p><span class="font-size-3"><a href="http://medium.com/@andrewjokeefe" target="_blank">Andrew J. O'Keefe II</a>, Media Producer</span></p><p><span class="font-size-3"><strong>Recommended reading:</strong> <a href="http://singularityhub.com/2016/02/16/how-ownerless-firms-will-soon-live-on-the-blockchain/" target="_blank">In the Future, Ownerless Companies Will Live on the Blockchain</a></span></p><h3><span class="font-size-3">4. Technology-Aided Learning</span></h3><p><span class="font-size-3">“Over the last few years there have been great cases of technology used to enhance classroom learning, like VR experiences that take students inside the bloodstream or into Darwin’s lab to assemble a skeleton. This year, Zuckerberg Education Ventures invested in <a href="http://www.volley.com/" target="_blank">Volley</a>, an AI learning assistant for students. The application provides students links to additional resources and highlights critical information when a user points their smartphone’s camera at a homework assignment or textbook page. In 2017, I’ll be watching for a new wave of AI applications focused on improving classroom learning for students with unique learning needs by providing resources like customized learning plans and personalized evaluations. Volley talks about ‘engineering for knowledge,’ and I’m hoping to see a lot more of this in the coming year.”</span></p><p><span class="font-size-3"><a href="http://medium.com/@DigitAlison" target="_blank">Alison E. Berman</a>, Staff Writer</span></p><p><span class="font-size-3"><strong>Recommended reading:</strong> <a href="http://singularityhub.com/2015/09/02/put-down-the-textbook-how-vr-is-reimagining-classroom-education/" target="_blank">Put Down the Textbook: How VR Is Reimagining Classroom Education</a></span></p><h3><span class="font-size-3">5. Global High-Speed Internet:</span></h3><p><span class="font-size-3">“In November, SpaceX submitted an application to the FCC to launch over 4,000 satellites into space to <a href="http://singularityhub.com/2016/11/21/the-race-to-wrap-the-earth-in-internet-is-heating-up/" target="_blank">envelop Earth in high-speed internet</a>, providing connectivity to even the most remote areas of the planet. If approved, SpaceX’s plan will pose serious competition to Google’s Project Loon, which has the same mission. Besides seeing which method has more success, it will be exciting to watch the effects of increased connectivity on the global population, particularly in developing nations that have yet to solve larger challenges related to education, healthcare, and access to natural resources.”</span></p><p><span class="font-size-3">Vanessa Bates Ramirez, Associate Editor</span></p><p><span class="font-size-3"><strong>Recommended reading:</strong></span></p><p><span class="font-size-3"><a href="http://singularityhub.com/2015/04/06/rising-billions-dramatic-positive-change/" target="_blank">Meet the Rising Billion Who Will Fuel Disruption in the Global Economy</a></span></p><p><span class="font-size-3"><a href="http://singularityhub.com/2016/11/21/the-race-to-wrap-the-earth-in-internet-is-heating-up/" target="_blank">The Race to Wrap the Earth in Internet Is Heating Up</a></span></p><h3><span class="font-size-3">6. Personal Synthetic Biology Lab</span></h3><p><span class="font-size-3">“I have a fantasy that one day in the future, I will be able to design, create and grow different types of biological products at home — anything from perfumes and medicine to cool materials like mushroom leather. The day when anyone can have an easy-to-use biological manufacturing facility at home is still a ways off, but the first step to that future is having something like the <a href="http://www.amino.bio/" target="_blank">Amino Lab</a> to learn bioengineering and start small, like making bacteria that grows.”</span></p><p><span class="font-size-3"><a href="http://medium.com/@svetamcshane" target="_blank">Sveta McShane</a>, Production Manager</span></p><p><span class="font-size-3"><strong>Recommended reading:</strong> <a href="http://singularityhub.com/2016/04/07/we-should-be-teaching-kids-to-code-biology-not-just-software/" target="_blank">Why We Should Teach Kids to Code Biology, Not Just Software</a></span></p><h3><span class="font-size-3">7. Machine Learning and Autonomous Vehicles</span></h3><p><span class="font-size-3">In 2017, we will truly begin to see the coming disruption self-driving vehicles will have on our society and future. <a href="http://github.com/commaai/openpilot" target="_blank">Open source machine learning agents</a>, more advanced algorithms, and <a href="http://singularityhub.com/2016/10/16/driverless-car-sensors-just-got-smaller-cheaper-and-better-all-at-once/" target="_blank">better hardware technologies</a> are bringing this autonomous reality closer. <a href="http://singularityhub.com/2016/10/21/teslas-are-teaching-each-other-how-to-drive-better-than-you/" target="_blank">Tesla has already said</a> vehicles now being produced have the hardware for level 5 autonomy capabilities (no need for steering wheel or brakes). Down the road, when the algorithm is ready, Tesla may make these cars autonomous with a software update.</span></p><p><span class="font-size-3">Kirk Nankivell, Web Production Editor</span></p></div>